Commentary on Antosz et al. (2023): The role of macro-micro-macro frameworks and critical realism in agent-based modelling.

Antosz and colleagues' review of the role of theory in agent-based modelling (ABM) makes important recommendations for modelling practitioners. However, macro-micro-macro frameworks are not necessarily as reliant on existing theory as the review suggests. Adopting a critical realist perspective to ABM design would help to deliver the recommendations, within which macro-micro-macro frameworks can play an important enabling role.

Simulation of Alcohol Control Policies for Health Equity (SIMAH) Project: Study Design and First Results.

Since about 2010, life expectancy at birth in the United States has stagnated and begun to decline, with concurrent increases in the socioeconomic divide in life expectancy. The Simulation of Alcohol Control Policies for Health Equity (SIMAH) Project uses a novel microsimulation approach to investigate the extent to which alcohol use, socioeconomic status (SES), and race/ethnicity contribute to unequal developments in US life expectancy and how alcohol control interventions could reduce such inequalities. Representative, secondary data from several sources will be integrated into one coherent, dynamic microsimulation to model life-course changes in SES and alcohol use and cause-specific mortality attributable to alcohol use by SES, race/ethnicity, age, and sex. Markov models will be used to inform transition intensities between levels of SES and drinking patterns. The model will be used to compare a baseline scenario with multiple counterfactual intervention scenarios. The preliminary results indicate that the crucial microsimulation component provides a good fit to observed demographic changes in the population, providing a robust baseline model for further simulation work. By demonstrating the feasibility of this novel approach, the SIMAH Project promises to offer superior integration of relevant empirical evidence to inform public health policy for a more equitable future.

The long-term effectiveness and cost-effectiveness of public health interventions; how can we model behavior? A review.

The effectiveness and cost of a public health intervention is dependent on complex human behaviors, yet health economic models typically make simplified assumptions about behavior, based on little theory or evidence. This paper reviews existing methods across disciplines for incorporating behavior within simulation models, to explore what methods could be used within health economic models and to highlight areas for further research. This may lead to better-informed model predictions. The most promising methods identified which could be used to improve modeling of the causal pathways of behavior-change interventions include econometric analyses, structural equation models, data mining and agent-based modeling; the latter of which has the advantage of being able to incorporate the non-linear, dynamic influences on behavior, including social and spatial networks. Twenty-two studies were identified which quantify behavioral theories within simulation models. These studies highlight the importance of combining individual decision making and interactions with the environment and demonstrate the importance of social norms in determining behavior. However, there are many theoretical and practical limitations of quantifying behavioral theory. Further research is needed about the use of agent-based models for health economic modeling, and the potential use of behavior maintenance theories and data mining.

Guidance on the use of complex systems models for economic evaluations of public health interventions.

To help health economic modelers respond to demands for greater use of complex systems models in public health. To propose identifiable features of such models and support researchers to plan public health modeling projects using these models. A working group of experts in complex systems modeling and economic evaluation was brought together to develop and jointly write guidance for the use of complex systems models for health economic analysis. The content of workshops was informed by a scoping review. A public health complex systems model for economic evaluation is defined as a quantitative, dynamic, non-linear model that incorporates feedback and interactions among model elements, in order to capture emergent outcomes and estimate health, economic and potentially other consequences to inform public policies. The guidance covers: when complex systems modeling is needed; principles for designing a complex systems model; and how to choose an appropriate modeling technique. This paper provides a definition to identify and characterize complex systems models for economic evaluations and proposes guidance on key aspects of the process for health economics analysis. This document will support the development of complex systems models, with impact on public health systems policy and decision making.

Can Social Norms Explain Long-Term Trends in Alcohol Use? Insights from Inverse Generative Social Science.

Social psychological theory posits entities and mechanisms that attempt to explain observable differences in behavior. For example, dual process theory suggests that an agent's behavior is influenced by intentional (arising from reasoning involving attitudes and perceived norms) and unintentional (i.e., habitual) processes. In order to pass the generative sufficiency test as an explanation of alcohol use, we argue that the theory should be able to explain notable patterns in alcohol use that exist in the population, e.g., the distinct differences in drinking prevalence and average quantities consumed by males and females. In this study, we further develop and apply inverse generative social science (iGSS) methods to an existing agent-based model of dual process theory of alcohol use. Using iGSS, implemented within a multi-objective grammar-based genetic program, we search through the space of model structures to identify whether a single parsimonious model can best explain both male and female drinking, or whether separate and more complex models are needed. Focusing on alcohol use trends in New York State, we identify an interpretable model structure that achieves high goodness-of-fit for both male and female drinking patterns simultaneously, and which also validates successfully against reserved trend data. This structure offers a novel interpretation of the role of norms in formulating drinking intentions, but the structure's theoretical validity is questioned by its suggestion that individuals with low autonomy would act against perceived descriptive norms. Improved evidence on the distribution of autonomy in the population is needed to understand whether this finding is substantive or is a modeling artefact.

A software architecture for mechanism-based social systems modelling in agent-based simulation models.

This paper introduces the MBSSM (Mechanism-Based Social Systems Modelling) software architecture that is designed for expressing mechanisms of social theories with individual behaviour components in a unified way and implementing these mechanisms in an agent-based simulation model. The MBSSM architecture is based on a middle-range theory approach most recently expounded by analytical sociology and is designed in the object-oriented programming paradigm with Unified Modelling Language diagrams. This paper presents two worked examples of using the architecture for modelling individual behaviour mechanisms that give rise to the dynamics of population-level alcohol use: a single-theory model of norm theory and a multi-theory model that combines norm theory with role theory. The MBSSM architecture provides a computational environment within which theories based on social mechanisms can be represented, compared, and integrated. The architecture plays a fundamental enabling role within a wider simulation model-based framework of abductive reasoning in which families of theories are tested for their ability to explain concrete social phenomena.

Typology and Dynamics of Heavier Drinking Styles in Great Britain: 1978-2010.

AIMS: To identify a typology of heavier drinking styles in Great Britain and to identify socio-demographic trends in the typology over the period 1978-2010. METHODS: We applied multiple correspondence analysis and agglomerative hierarchical clustering to beverage-specific quantity-frequency measures of alcohol consumption in the repeated cross-sectional General Lifestyle Survey of Great Britain, 1978-2010. The cluster analysis focuses on the 60,043 adult respondents over this period reporting average drinking levels above the UK Government guidelines. We projected sex, age, income, education, socio-economic status and tobacco consumption variables onto the clusters to inspect socio-demographic trends in heavier drinking. RESULTS: We identified four stable clusters of heavier drinking: (a) high volume beer; (b) beer and spirit combination; (c) all beverage and (d) wine and spirit only. The socio-demographic characteristics of the clusters were distinct from both each other and the general population. However, all clusters had higher median incomes and higher smoking rates than the population. Increases in the prevalence of heavier drinking were driven by a 5-fold increase in the contribution of the female-dominated, wine and spirit only cluster. CONCLUSIONS: Recent changes in per capita alcohol consumption in Great Britain occurred within the context of a stable typology of heavier drinking styles and shifting socio-demographics. Identifying these trends is essential to better understand how drinking cultures develop over time and where potentially problematic drinking styles may emerge. Our findings suggest that careful attention to patterns and cultures of consumption is more important than relying on headline consumption data, for both understanding drinking behaviours and targeting interventions. SHORT SUMMARY: This analysis of alcohol consumption survey data identifies four styles of heavier drinking in Great Britain, which remain unchanged over the period 1978-2010. The socio-demographic characteristics of the drinking styles are distinct from both each other and the general population, with increased participation of female and older drinkers over time.

Effects of minimum unit pricing for alcohol on different income and socioeconomic groups: a modelling study.

BACKGROUND: Several countries are considering a minimum price policy for alcohol, but concerns exist about the potential effects on drinkers with low incomes. We aimed to assess the effect of a £0·45 minimum unit price (1 unit is 8 g/10 mL ethanol) in England across the income and socioeconomic distributions. METHODS: We used the Sheffield Alcohol Policy Model (SAPM) version 2.6, a causal, deterministic, epidemiological model, to assess effects of a minimum unit price policy. SAPM accounts for alcohol purchasing and consumption preferences for population subgroups including income and socioeconomic groups. Purchasing preferences are regarded as the types and volumes of alcohol beverages, prices paid, and the balance between on-trade (eg, bars) and off-trade (eg, shops). We estimated price elasticities from 9 years of survey data and did sensitivity analyses with alternative elasticities. We assessed effects of the policy on moderate, hazardous, and harmful drinkers, split into three socioeconomic groups (living in routine or manual households, intermediate households, and managerial or professional households). We examined policy effects on alcohol consumption, spending, rates of alcohol-related health harm, and opportunity costs associated with that harm. Rates of harm and costs were estimated for a 10 year period after policy implementation. We adjusted baseline rates of mortality and morbidity to account for differential risk between socioeconomic groups. FINDINGS: Overall, a minimum unit price of £0.45 led to an immediate reduction in consumption of 1.6% (-11.7 units per drinker per year) in our model. Moderate drinkers were least affected in terms of consumption (-3.8 units per drinker per year for the lowest income quintile vs 0.8 units increase for the highest income quintile) and spending (increase in spending of £0.04 vs £1.86 per year). The greatest behavioural changes occurred in harmful drinkers (change in consumption of -3.7% or -138.2 units per drinker per year, with a decrease in spending of £4.01), especially in the lowest income quintile (-7.6% or -299.8 units per drinker per year, with a decrease in spending of £34.63) compared with the highest income quintile (-1.0% or -34.3 units, with an increase in spending of £16.35). Estimated health benefits from the policy were also unequally distributed. Individuals in the lowest socioeconomic group (living in routine or manual worker households and comprising 41.7% of the sample population) would accrue 81.8% of reductions in premature deaths and 87.1% of gains in terms of quality-adjusted life-years. INTERPRETATION: Irrespective of income, moderate drinkers were little affected by a minimum unit price of £0.45 in our model, with the greatest effects noted for harmful drinkers. Because harmful drinkers on low incomes purchase more alcohol at less than the minimum unit price threshold compared with other groups, they would be affected most by this policy. Large reductions in consumption in this group would however coincide with substantial health gains in terms of morbidity and mortality related to reduced alcohol consumption. FUNDING: UK Medical Research Council and Economic and Social Research Council (grant G1000043).

The Sheffield Alcohol Policy Model - A Mathematical Description.

This methodology paper sets out a mathematical description of the Sheffield Alcohol Policy Model version 2.0, a model to evaluate public health strategies for alcohol harm reduction in the UK. Policies that can be appraised include a minimum price per unit of alcohol, restrictions on price discounting, and broader public health measures. The model estimates the impact on consumers, health services, crime, employers, retailers and government tax revenues. The synthesis of public and commercial data sources to inform the model structure is described. A detailed algebraic description of the model is provided. This involves quantifying baseline levels of alcohol purchasing and consumption by age and gender subgroups, estimating the impact of policies on consumption, for example, using evidence on price elasticities of demand for alcohol, quantification of risk functions relating alcohol consumption to harms including 47 health conditions, crimes, absenteeism and unemployment, and finally monetary valuation of the consequences. The results framework, shown for a minimum price per unit of alcohol, has been used to provide policy appraisals for the UK government policy-makers. In discussion and online appendix, we explore issues around valuation and scope, limitations of evidence/data, how the framework can be adapted to other countries and decisions, and ongoing plans for further development. © 2014 The Authors. Health Economics published by John Wiley & Sons Ltd.

Cost-effectiveness of a programme of screening and brief interventions for alcohol in primary care in Italy.

BACKGROUND: As alcohol-related health problems continue to rise, the attention of policy-makers is increasingly turning to Screening and Brief Intervention (SBI) programmes. The effectiveness of such programmes in primary healthcare is well evidenced, but very few cost-effectiveness analyses have been conducted and none which specifically consider the Italian context. METHODS: The Sheffield Alcohol Policy Model has been used to model the cost-effectiveness of government pricing and public health policies in several countries including England. This study adapts the model using Italian data to evaluate a programme of screening and brief interventions in Italy. Results are reported as Incremental Cost-Effectiveness Ratios (ICERs) of SBI programmes versus a 'do-nothing' scenario. RESULTS: Model results show such programmes to be highly cost-effective, with estimated ICERs of €550/Quality Adjusted Life Year (QALY) gained for a programme of SBI at next GP registration and €590/QALY for SBI at next GP consultation. A range of sensitivity analyses suggest these results are robust under all but the most pessimistic assumptions. CONCLUSIONS: This study provides strong support for the promotion of a policy of screening and brief interventions throughout Italy, although policy makers should be aware of the resource implications of different implementation options.

How can agent-based modelling provide new insights into the impact of minimum unit pricing in Scotland?

In recent years we have gained insight into the impact of minimum unit pricing (MUP)-a legal floor price below which a given volume of alcohol cannot be sold-on population-level reductions in alcohol sales, consumption and harm. However, several questions remain unanswered including how individual-level purchasing changes impact the local economy (e.g., balance between on-licence and off-licence outlets), lead to long-term population-level trends (e.g., youth drinking) and social harms (e.g., violence). Agent-based modelling captures heterogeneity, emergence, feedback loops and adaptive and dynamic features, which provides an opportunity to understand the nuanced effects of MUP. Agent-based models (ABM) simulate heterogeneous agents (e.g., individuals, organisations) often situated in space and time that interact with other agents and/or with their environment, allowing us to identify the mechanisms underlying social phenomena. ABMs are particularly useful for theory development, and testing and simulating the impacts of policies and interventions. We illustrate how ABMs could be applied to generate novel insights and provide best estimates of social network effects, and changes in purchasing behaviour and social harms, due to the implementation of MUP. ABMs like other modelling approaches can simulate alternative implementations of MUP (e.g., policy intensity [£0.50, £0.60] or spatial scales [local, national]) but can also provide an understanding of the potential impact of MUP on different population groups (e.g., alcohol exposure of young people who are not yet drinking). Using ABMs to understand the impact of MUP would provide new insights to complement those from traditional epidemiological and other modelling methods.

Adjusting for unrecorded consumption in survey and per capita sales data: quantification of impact on gender- and age-specific alcohol-attributable fractions for oral and pharyngeal cancers in Great Britain.

AIMS: Large discrepancies are typically found between per capita alcohol consumption estimated via survey data compared with sales, excise or production figures. This may lead to significant inaccuracies when calculating levels of alcohol-attributable harms. Using British data, we demonstrate an approach to adjusting survey data to give more accurate estimates of per capita alcohol consumption. METHODS: First, sales and survey data are adjusted to account for potential biases (e.g. self-pouring, under-sampled populations) using evidence from external data sources. Secondly, survey and sales data are aligned using different implementations of Rehm et al.'s method [in (2010) Statistical modeling of volume of alcohol exposure for epidemiological studies of population health: the US example. Pop Health Metrics 8, 1-12]. Thirdly, the impact of our approaches is tested by using our revised survey dataset to calculate alcohol-attributable fractions (AAFs) for oral and pharyngeal cancers. RESULTS: British sales data under-estimate per capita consumption by 8%, primarily due to illicit alcohol. Adjustments to survey data increase per capita consumption estimates by 35%, primarily due to under-sampling of dependent drinkers and under-estimation of home-poured spirits volumes. Before aligning sales and survey data, the revised survey estimate remains 22% lower than the revised sales estimate. Revised AAFs for oral and pharyngeal cancers are substantially larger with our preferred method for aligning data sources, yielding increases in an AAF from the original survey dataset of 0.47-0.60 (males) and 0.28-0.35 (females). CONCLUSION: It is possible to use external data sources to adjust survey data to reduce the under-estimation of alcohol consumption and then account for residual under-estimation using a statistical calibration technique. These revisions lead to markedly higher estimated levels of alcohol-attributable harm.

Modelling the cost-effectiveness of alcohol screening and brief interventions in primary care in England.

AIMS: To estimate the cost-effectiveness and resourcing implications of universal alcohol screening and brief intervention (SBI) programmes in primary care in England. METHODS: This was a health economic model, combining evidence of the effectiveness and health care resource requirements of SBI activities with existing epidemiological modelling of the relationship between alcohol consumption and health harms. RESULTS: Screening patients on registration with a family doctor would steadily capture ~40% of the population over a 10-year programme; screening patients at next primary care consultation would capture 96% of the population over the same period, but with high resourcing needs in the first year. The registration approach, delivered by a practice nurse, provides modest cost savings to the health care system of £120 m over 30 years. Health gains over the same period amount to 32,000 quality-adjusted life years (QALYs). This SBI programme still appears cost-effective (at £6900 per QALY gained) compared with no programme, under pessimistic effectiveness assumptions. Switching to a consultation approach, delivered by a doctor, would incur an incremental net cost of £108 m, with incremental health gains equivalent to 92,000 QALYs, giving an incremental cost-effectiveness ratio of £1175 per QALY gained compared with current practice. CONCLUSION: A universal programme of alcohol SBI in primary care is estimated to be cost-effective, under all but the most pessimistic assumptions for programme costs and effectiveness. Policymakers should ensure that SBI programmes are routinely evaluated and followed up, given the substantial uncertainty over the effects of many of the implementation details.

Behavioral stability of alcohol consumption and socio-demographic correlates of change among a nationally representative cohort of US adults.

AIMS: To estimate the probability of transitioning between different categories of alcohol use (drinking states) among a nationally representative cohort of United States (US) adults and to identify the effects of socio-demographic characteristics on those transitions. DESIGN, SETTING AND PARTICIPANTS: Secondary analysis of data from the National Epidemiologic Survey of Alcohol and Related Conditions (NESARC), a prospective cohort study conducted in 2001-02 and 2004-05; a US nation-wide, population-based study. Participants included 34 165 adults (mean age = 45.1 years, standard deviation = 17.3; 52% women). MEASUREMENTS: Alcohol use was self-reported and categorized based on the grams consumed per day: (1) non-drinker (no drinks in past 12 months), (2) category I (women = ≤ 20; men = ≤ 40), (3) category II (women = 21-40; men = 41-60) and (4) category III (women = ≥ 41; men = ≥ 61). Multi-state Markov models estimated the probability of transitioning between drinking states, conditioned on age, sex, race/ethnicity and educational attainment. Analyses were repeated with alcohol use categorized based on the frequency of heavy episodic drinking. FINDINGS: The highest transition probabilities were observed for staying in the same state; after 1 year, the probability of remaining in the same state was 90.1% [95% confidence interval (CI) = 89.7%, 90.5%] for non-drinkers, 90.2% (95% CI = 89.9%, 90.5%) for category I, 31.8% (95% CI = 29.7, 33.9%) category II and 52.2% (95% CI = 46.0, 58.5%) for category III. Women, older adults, and non-Hispanic Other adults were less likely to transition between drinking states, including transitions to lower use. Adults with lower educational attainment were more likely to transition between drinking states; however, they were also less likely to transition out of the 'weekly HED' category. Black adults were more likely to transition into or stay in higher use categories, whereas Hispanic/Latinx adults were largely similar to White adults. CONCLUSIONS: In this study of alcohol transition probabilities, some demographic subgroups appeared more likely to transition into or persist in higher alcohol consumption states.

A synthetic population dataset for estimating small area health and socio-economic outcomes in Great Britain.

In order to understand the health outcomes for distinct sub-groups of the population or across different geographies, it is advantageous to be able to build bespoke groupings from individual level data. Individuals possess distinct characteristics, exhibit distinct behaviours and accumulate their own unique history of exposure or experiences. However, in most disciplines, not least public health, there is a lack of individual level data available outside of secure settings, especially covering large portions of the population. This paper provides detail on the creation of a synthetic micro dataset for individuals in Great Britain who have detailed attributes which can be used to model a wide range of health and other outcomes. These attributes are constructed from a range of sources including the United Kingdom Census, survey and administrative datasets. It provides a rationale for the need for this synthetic population, discusses methods for creating this dataset and provides some example results of different attribute distributions for distinct sub-population groups and over different geographical areas.

Improved estimates for individual and population-level alcohol use in the United States, 1984-2020.

Aims: While nationally representative alcohol surveys are a mainstay of public health monitoring, they underestimate consumption at the population level. This paper demonstrates how to adjust individual-level survey data using aggregated alcohol per capita (APC) data for improved individual- and population-level consumption estimates. Design and Methods: For the period 1984-2020, data on self-reported alcohol consumption in the past 30 days were taken from the Behavioral Risk Factor Surveillance System (BRFSS) involving participants (18+ years) in the United States (US). Monthly abstainers were reallocated into lifetime abstainers, former drinkers, and 12-month drinkers using the 2005 National Alcohol Survey data. To correct for under-coverage of alcohol use, we triangulated APC and survey data by upshifting quantity (average grams/day) and frequency (drinking days/week) of alcohol use based on national- and state-level APC data. Results were provided for the US as a whole and for selected states to represent different drinking patterns. Findings: The corrections described above resulted in improved correspondence between survey and APC data. Following our procedure, national estimates of alcohol quantity increased from 45% to 77% of APC estimates. Both quantity and frequency of alcohol use were upshifted; by upshifting to 90% of APC, we were able to fit trends and distributions in APC patterns for individual states and the US. Conclusions: An individual-level dataset which more accurately reflects the alcohol use of US citizens was achieved. This dataset will be invaluable as a research tool and for the planning and evaluation of alcohol control policies for the US. The methodology described can also be used to adjust individual-level alcohol survey data in other geographical settings.

Causal mechanisms proposed for the alcohol harm paradox-a systematic review.

BACKGROUND AND AIMS: The alcohol harm paradox (AHP) posits that disadvantaged groups suffer from higher rates of alcohol-related harm compared with advantaged groups, despite reporting similar or lower levels of consumption on average. The causes of this relationship remain unclear. This study aimed to identify explanations proposed for the AHP. Secondary aims were to review the existing evidence for those explanations and investigate whether authors linked explanations to one another. METHODS: This was a systematic review. We searched MEDLINE (1946-January 2021), EMBASE (1974-January 2021) and PsycINFO (1967-January 2021), supplemented with manual searching of grey literature. Included papers either explored the causes of the AHP or investigated the relationship between alcohol consumption, alcohol-related harm and socio-economic position. Papers were set in Organization for Economic Cooperation and Development high-income countries. Explanations extracted for analysis could be evidenced in the empirical results or suggested by researchers in their narrative. Inductive thematic analysis was applied to group explanations. RESULTS: Seventy-nine papers met the inclusion criteria and initial coding revealed that these papers contained 41 distinct explanations for the AHP. Following inductive thematic analysis, these explanations were grouped into 16 themes within six broad domains: individual, life-style, contextual, disadvantage, upstream and artefactual. Explanations related to risk behaviours, which fitted within the life-style domain, were the most frequently proposed (n = 51) and analysed (n = 21). CONCLUSIONS: While there are many potential explanations for the alcohol harm paradox, most research focuses on risk behaviours while other explanations lack empirical testing.

An integrated dual process simulation model of alcohol use behaviours in individuals, with application to US population-level consumption, 1984-2012.

INTRODUCTION: The Theory of Planned Behaviour (TPB) describes how attitudes, norms and perceived behavioural control guide health behaviour, including alcohol consumption. Dual Process Theories (DPT) suggest that alongside these reasoned pathways, behaviour is influenced by automatic processes that are determined by the frequency of engagement in the health behaviour in the past. We present a computational model integrating TPB and DPT to determine drinking decisions for simulated individuals. We explore whether this model can reproduce historical patterns in US population alcohol use and simulate a hypothetical scenario, "Dry January", to demonstrate the utility of the model for appraising the impact of policy interventions on population alcohol use. METHOD: Constructs from the TPB pathway were computed using equations from an existing individual-level dynamic simulation model of alcohol use. The DPT pathway was initialised by simulating individuals' past drinking using data from a large US survey. Individuals in the model were from a US population microsimulation that accounts for births, deaths and migration (1984-2015). On each modelled day, for each individual, we calculated standard drinks consumed using the TPB or DPT pathway. In each year we computed total population alcohol use prevalence, frequency and quantity. The model was calibrated to alcohol use data from the Behavioral Risk Factor Surveillance System (1984-2004). RESULTS: The model was a good fit to prevalence and frequency but a poorer fit to quantity of alcohol consumption, particularly in males. Simulating Dry January in each year led to a small to moderate reduction in annual population drinking. CONCLUSION: This study provides further evidence, at the whole population level, that a combination of reasoned and implicit processes are important for alcohol use. Alcohol misuse interventions should target both processes. The integrated TPB-DPT simulation model is a useful tool for estimating changes in alcohol consumption following hypothetical population interventions.

Estimated effect of alcohol pricing policies on health and health economic outcomes in England: an epidemiological model.

BACKGROUND: Although pricing policies for alcohol are known to be effective, little is known about how specific interventions affect health-care costs and health-related quality-of-life outcomes for different types of drinkers. We assessed effects of alcohol pricing and promotion policy options in various population subgroups. METHODS: We built an epidemiological mathematical model to appraise 18 pricing policies, with English data from the Expenditure and Food Survey and the General Household Survey for average and peak alcohol consumption. We used results from econometric analyses (256 own-price and cross-price elasticity estimates) to estimate effects of policies on alcohol consumption. We applied risk functions from systemic reviews and meta-analyses, or derived from attributable fractions, to model the effect of consumption changes on mortality and disease prevalence for 47 illnesses. FINDINGS: General price increases were effective for reduction of consumption, health-care costs, and health-related quality of life losses in all population subgroups. Minimum pricing policies can maintain this level of effectiveness for harmful drinkers while reducing effects on consumer spending for moderate drinkers. Total bans of supermarket and off-license discounting are effective but banning only large discounts has little effect. Young adult drinkers aged 18-24 years are especially affected by policies that raise prices in pubs and bars. INTERPRETATION: Minimum pricing policies and discounting restrictions might warrant further consideration because both strategies are estimated to reduce alcohol consumption, and related health harms and costs, with drinker spending increases targeting those who incur most harm. FUNDING: Policy Research Programme, UK Department of Health.

Causality and initiation of alcohol control policy. A response to Allamani.

In a recent commentary, Allamani asked how one can establish causality in epidemiological research, and specifically about causality as it relates to alcohol control policy. Epidemiology customarily uses a sufficient-component cause model, where a sufficient cause for an outcome is determined by a set of minimal conditions and events that inevitably produce the stated outcome. While this model is theoretically clear, its operationalisation often involves probabilistic elements. Recent advances in agent-based modelling may improve operationalisation. The implications for alcohol control policy from this model are straightforward: the so-called alcohol-attributable fraction denotes the cases of morbidity or mortality which would not have happened in the absence of alcohol use.